This paper investigates the prediction of Value-at-Risk (VaR) using option-implied information obtained by the maximum entropy method. The maximum entropy method provides an estimate of the risk-neutral distribution based on option prices. Besides commonly used implied volatility, we obtain...

In this paper, we propose a test for the multivariate regular variation model. The test is based on testing whether the extreme value indices of the radial component conditional on the angular component falling in different subsets are the same. Combining the test on the constancy across...

This paper studies the detection of outliers in risk indicators based on large value payment system transaction data. The ten risk indicators are daily time series measuring various risks in the large value payment system, such as operational risk, concentration risk and liquidity flows related...

We consider extreme value analysis in a semi-supervised setting, where we observe, next to the n data on the target variable, n +m data on one or more covariates. This is called the semi-supervised model with n labeled and m unlabeled data. By exploiting the tail dependence between the target...

This paper examines the predictive power of weather for electricity prices in day ahead markets in real time. We find that next-day weather forecasts improve the forecast accuracy of Scandinavian day-ahead electricity prices substantially in terms of point forecasts, suggesting that weather...

Denote the loss return on the equity of a financial institution as X and that of the entire market as Y . For a given very small value of p 0, the marginal expected shortfall (MES) is defined as E(X | Y QY (1−p)), where QY (1−p) is the (1−p)-th quantile of the distribution of Y . The MES...